Python general function to realize array calculation

1、 Operation of array

Array operations can be added, subtracted, multiplied and divided. At the same time, these arithmetic operators can be arbitrarily combined to achieve the effect.

>>> x=np.arange(5)
>>> x
array([0, 1, 2, 3, 4])
>>> x=5
>>> x=np.arange(5)
>>> x+5
array([5, 6, 7, 8, 9])
>>> x-5
array([-5, -4, -3, -2, -1])
>>> x*2
array([0, 2, 4, 6, 8])
>>> x/2
array([0. , 0.5, 1. , 1.5, 2. ])
>>> x//2
array([0, 0, 1, 1, 2], dtype=int32)

2、 Operation of absolute value

There are three methods in total. The first method is to directly use ABS function which is not numpy library for calculation. The second and third methods are to use ABS function and absolute function of numpy library for calculation. As follows:

>>> x=np.array([1,2,3,-4,-5,-6])
>>> x
array([ 1,  2,  3, -4, -5, -6])
>>> abs(x)
array([1, 2, 3, 4, 5, 6])
>>> np.abs(x)
array([1, 2, 3, 4, 5, 6])
>>> np.absolute(x)
array([1, 2, 3, 4, 5, 6])

3、 The operation of trigonometric function

First, define an array object in NP of a, and then perform the operation

>>> a
array([0.        , 1.57079633, 3.14159265])
>>> np.sin(a)
array([0.0000000e+00, 1.0000000e+00, 1.2246468e-16])
>>> np.cos(a)
array([ 1.000000e+00,  6.123234e-17, -1.000000e+00])
>>> np.tan(a)
array([ 0.00000000e+00,  1.63312394e+16, -1.22464680e-16])

4、 Operation of exponent and logarithm

Operation of index:

>>> x=[1,2,3]
>>> x
[1, 2, 3]
>>> np.exp(x)
array([ 2.71828183,  7.3890561 , 20.08553692])
>>> np.exp2(x)
array([2., 4., 8.])

np.power(3,x)
array([ 3,  9, 27], dtype=int32)

Operation of logarithm:

>>> np.log(x)
array([0.        , 0.69314718, 1.09861229])
>>> np.log2(x)
array([0.       , 1.       , 1.5849625])
>>> x
[1, 2, 3]
>>> np.log10(x)
array([0.        , 0.30103   , 0.47712125])